From 827b0d0e755ada128e6df8061e12948741562681 Mon Sep 17 00:00:00 2001 From: Kyle Dunovan | Ntrepid Corp Date: Thu, 28 Feb 2019 17:15:28 -0500 Subject: [PATCH 1/2] update --- radd/__init__.py | 27 ++++++++++++++++++++++++--- radd/dfhandler.py | 10 +++++++--- radd/models.py | 1 + 3 files changed, 32 insertions(+), 6 deletions(-) diff --git a/radd/__init__.py b/radd/__init__.py index 82bae07..9582181 100644 --- a/radd/__init__.py +++ b/radd/__init__.py @@ -7,11 +7,32 @@ _package_dir = os.path.dirname(os.path.realpath(__file__)) __version__ = '0.2.3' -def load_example_data(): +def load_example_data(name='elife'): + """ load example data from elife (2015) or jneuro (2018) publications + ::Arguments:: + name (str): 'elife', 'elife_pro', or 'jneuro' + ::Returns:: + pandas dataframe with behavioral data from elife or jneuro pubs + """ import pandas as pd - _examples_dir = os.path.join(_package_dir, 'examples') - data_fpath = os.path.join(_examples_dir, 'reactive_example_idx.csv') + if 'elife' in name: + data_dir = os.path.join(_package_dir, 'datasets/eLife15') + if 'pro' in name: + data_fpath = os.path.join(data_dir, 'pro_stop_data.csv') + else: + # 're_stop_data.csv' + data_fpath = os.path.join(data_dir, 're_stop_data.csv') #'elife2015_example_data.csv') + elif name == 'jneuro': + data_dir = os.path.join(_package_dir, 'datasets/jNeuro18') + data_fpath = os.path.join(data_dir, 'adaptive_ss_behavior.csv') return pd.read_csv(data_fpath).copy() +# +# +# def load_example_data(): +# import pandas as pd +# _examples_dir = os.path.join(_package_dir, 'examples') +# data_fpath = os.path.join(_examples_dir, 'reactive_example_idx.csv') +# return pd.read_csv(data_fpath).copy() def load_dpm_animation(): import io, base64 diff --git a/radd/dfhandler.py b/radd/dfhandler.py index 37a2c2c..562b80d 100644 --- a/radd/dfhandler.py +++ b/radd/dfhandler.py @@ -76,7 +76,7 @@ def make_observed_groupDFs(self): index = range(nrows) nan_data = np.zeros((nrows, ncols))*np.nan - self.datdf = self.grpData.apply(self.rangl_data).sortlevel(0) + self.datdf = self.grpData.apply(self.rangl_data).sort_index(0) self.dfvals = self.datdf.values self.observedDF = pd.DataFrame(nan_data, columns=masterDF_header, index=index) self.observedDF.loc[:, self.groups] = self.datdf.reset_index()[self.groups].values @@ -236,6 +236,10 @@ def idx_quant_weights(self): QSEM = mjci(rtvectors) wts = median(QSEM)/QSEM """ + if self.model.kind=='pro': + n = 1 + else: + n = 2 idx_mjci = lambda x: mjci(x.rt, prob=self.model.quantiles) nidx = self.nidx nquant = self.model.quantiles.size @@ -249,7 +253,7 @@ def idx_quant_weights(self): # apply self.idx_mjci() to estimate quantile CI's quant_err = np.vstack(godf_grouped.apply(idx_mjci).values) # reshape [nidx x ncond * nquant * nacc] - idx_qerr = quant_err.reshape(nidx, nsplits * nquant * 2) + idx_qerr = quant_err.reshape(nidx, nsplits * nquant * n) # calculate subject median across all conditions quantiles and accuracy # this implicitly accounts for n_obs as the mjci estimate of sem will be lower # for conditions with greater number of observations (i.e., more acc==1 in godf) @@ -258,7 +262,7 @@ def idx_quant_weights(self): # set extreme values to max_wt arg val idx_qratio[idx_qratio >= self.max_wt] = self.max_wt # reshape to fit in wtsDF[:, q_cols] - return idx_qratio.reshape(nidx * nsplits, nquant * 2) + return idx_qratio.reshape(nidx * nsplits, nquant * n) def idx_acc_weights(self, index=['idx']): """ count number of observed responses across levels, transform into ratios diff --git a/radd/models.py b/radd/models.py index 9e355f3..8220672 100644 --- a/radd/models.py +++ b/radd/models.py @@ -18,6 +18,7 @@ def __init__(self, fitparams=None, pc_map=None, kind='xdpm', dt=.005, si=.01, le self.fitparams = fitparams self.pc_map = pc_map self.kind = kind + self.include_ss=False if 'ssd_info' in fitparams.keys(): self.ssd_info = fitparams['ssd_info'] self.include_ss=True From 8e39b099ef5662a5af66a54142b08aac55025d5a Mon Sep 17 00:00:00 2001 From: Kyle Dunovan | Ntrepid Corp Date: Thu, 28 Feb 2019 17:16:01 -0500 Subject: [PATCH 2/2] update --- radd/datasets/.DS_Store | Bin 0 -> 6148 bytes .../eLife15/elife2015_example_data.csv | 6631 ++++ radd/datasets/eLife15/pro_stop_data.csv | 31355 ++++++++++++++++ radd/datasets/eLife15/re_stop_data.csv | 26963 +++++++++++++ 4 files changed, 64949 insertions(+) create mode 100644 radd/datasets/.DS_Store create mode 100644 radd/datasets/eLife15/elife2015_example_data.csv create mode 100644 radd/datasets/eLife15/pro_stop_data.csv create mode 100644 radd/datasets/eLife15/re_stop_data.csv diff --git a/radd/datasets/.DS_Store b/radd/datasets/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..1332ca34dd99b440d3ff0d1239454a1ed9ce793f GIT binary patch literal 6148 zcmeHK%}yIJ5Vk`~HmXo_Kq5z9I3VSa zl&q%$$n_i%bJ><0Wqp~d0c~@Hdvr@^-4&;|O8XeV^Kd3Yh;xroQr{_w_3_wky>E#1jqOQ8j9X2&AvRmvlS$QCS#@{zk9$AQ#}|`d 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